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2. North Atlantic climate far more predictable than models imply

Author

Smith, D. M., Scaife, A. A., Eade, R., Athanasiadis, P., Bellucci, A., Bethke, I., Bilbao, R., Borchert, L. F., Caron, L.-P., Counillon, F., Danabasoglu, G., Delworth, T., Doblas-Reyes, F. J., Dunstone, N. J., Estella-Perez, V., Flavoni, S., Hermanson, L., Keenlyside, N., Kharin, V., Kimoto, M., Merryfield, W. J., Mignot, J., Mochizuki, T., Modali, K., Monerie, P.-A., Müller, W. A., Nicolí, D., Ortega, P., Pankatz, K., Pohlmann, H., Robson, J., Ruggieri, P., Sospedra-Alfonso, R., Swingedouw, D., Wang, Y., Wild, S., Yeager, S., Yang, X., and Zhang, L.

Published
2020
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3. North Atlantic climate far more predictable than models imply

Author

Barcelona Supercomputing Center, Smith, Doug, Scaife, Adam A., Athanasiadis, P., Bellucci, A., Bethke, Ingo, Bilbao, Roberto, Borchert, Leonard F., Caron, Louis-Philippe, Counillon, F., Danabasoglu, G., Delworth, Thomas, Doblas-Reyes, Francisco, Dunstone, Nick, Estella-Perez, V., Flavoni, S., Hermanson, Leon, Keenlyside, Noel, Kharin, V., Kimoto, M., Merryfield, W.J., Mignot, Juliette, Mochizuki, T., Modali, K., Monerie, P.-A., Müller, W.A., Nicolí, Dario, Ortega Montilla, Pablo, Pankatz, K., Pohlmann, H., Robson, Jon, Ruggieri, P., Sospedra-Alfonso, Reinel, Swingedouw, Didier, Wang, Yiguo, Wild, Simon, Yeager, Stephen, Yang, Xiaosong, Liping, Zhang, Barcelona Supercomputing Center, Smith, Doug, Scaife, Adam A., Athanasiadis, P., Bellucci, A., Bethke, Ingo, Bilbao, Roberto, Borchert, Leonard F., Caron, Louis-Philippe, Counillon, F., Danabasoglu, G., Delworth, Thomas, Doblas-Reyes, Francisco, Dunstone, Nick, Estella-Perez, V., Flavoni, S., Hermanson, Leon, Keenlyside, Noel, Kharin, V., Kimoto, M., Merryfield, W.J., Mignot, Juliette, Mochizuki, T., Modali, K., Monerie, P.-A., Müller, W.A., Nicolí, Dario, Ortega Montilla, Pablo, Pankatz, K., Pohlmann, H., Robson, Jon, Ruggieri, P., Sospedra-Alfonso, Reinel, Swingedouw, Didier, Wang, Yiguo, Wild, Simon, Yeager, Stephen, Yang, Xiaosong, and Liping, Zhang

Abstract

Quantifying signals and uncertainties in climate models is essential for the detection, attribution, prediction and projection of climate change1,2,3. Although inter-model agreement is high for large-scale temperature signals, dynamical changes in atmospheric circulation are very uncertain4. This leads to low confidence in regional projections, especially for precipitation, over the coming decades5,6. The chaotic nature of the climate system7,8,9 may also mean that signal uncertainties are largely irreducible. However, climate projections are difficult to verify until further observations become available. Here we assess retrospective climate model predictions of the past six decades and show that decadal variations in North Atlantic winter climate are highly predictable, despite a lack of agreement between individual model simulations and the poor predictive ability of raw model outputs. Crucially, current models underestimate the predictable signal (the predictable fraction of the total variability) of the North Atlantic Oscillation (the leading mode of variability in North Atlantic atmospheric circulation) by an order of magnitude. Consequently, compared to perfect models, 100 times as many ensemble members are needed in current models to extract this signal, and its effects on the climate are underestimated relative to other factors. To address these limitations, we implement a two-stage post-processing technique. We first adjust the variance of the ensemble-mean North Atlantic Oscillation forecast to match the observed variance of the predictable signal. We then select and use only the ensemble members with a North Atlantic Oscillation sufficiently close to the variance-adjusted ensemble-mean forecast North Atlantic Oscillation. This approach greatly improves decadal predictions of winter climate for Europe and eastern North America. Predictions of Atlantic multidecadal variability are also improved, suggesting that the North Atlantic Oscillation is not driven, DMS, AAS, NJD, LH and RE were supported by the Met Office Hadley Centre Climate Programme funded by BEIS and Defra and by the European Commission Horizon 2020 EUCP project (GA 776613). FJDR, LPC, SW and RB also acknowledge the support from the EUCP project (GA 776613) and from the Ministerio de Econom´ıa y Competitividad (MINECO) as part of the CLINSA project (Grant No. CGL2017-85791-R). SW received funding from the innovation programme under the Marie Sk´lodowska-Curie grant agreement H2020-MSCA-COFUND-2016-754433 and PO from the Ramon y Cajal senior tenure programme of MINECO. The EC-Earth simulations were performed on Marenostrum 4 (hosted by the Barcelona Supercomputing Center, Spain) using Auto-Submit through computing hours provided by PRACE.WAM, HP, KMand KP were supported by the German FederalMinistry for Education and Research (BMBF) project MiKlip (grant 01LP1519A). NK, IB, FC and YW were supported by the Norwegian Research Council projects SFE (grant 270733) the Nordic Center of excellent ARCPATH (grant 76654) and the Trond Mohn Foundation, under the project number : BFS2018TMT01 and received grants for computer time from the Norwegian Program for supercomputing (NOTUR2, NN9039K) and storage grants (NORSTORE, NS9039K). JM, LFB and DS are supported by Blue-Action (European Union Horizon 2020 research and innovation program, Grant Number: 727852) and EUCP (European Union Horizon 2020 research and innovation programme under grant agreement no 776613) projects. The National Center for Atmospheric Research (NCAR) is a major facility sponsored by the US National Science Foundation (NSF) under Cooperative Agreement No. 1852977. NCAR contribution was partially supported by the National Oceanic and Atmospheric Administration (NOAA) Climate Program Office under Climate Variability and Predictability Program Grant NA13OAR4310138 and by the US NSF Collaborative Research EaSM2 Grant OCE-1243015., Peer Reviewed, Postprint (author's final draft)

Published
2020

4. En el postprint el titulo es: Climate models underpredict North Atlantic atmospheric circulation changes

Author

Wolfgang A. Müller, Leon Hermanson, Reinel Sospedra-Alfonso, Stephen Yeager, Adam A. Scaife, Holger Pohlmann, Gokhan Danabasoglu, Roberto Bilbao, William J. Merryfield, Masahide Kimoto, Jon Robson, Pablo Ortega, Leonard Borchert, Rosie Eade, Paolo Ruggieri, Klaus Pankatz, Victor Estella-Perez, Ingo Bethke, Dario Nicolì, Yiguo Wang, Simon Wild, Kameswarrao Modali, Takashi Mochizuki, Doug Smith, Alessio Bellucci, Xiaosong Yang, Nick Dunstone, Noel Keenlyside, Francois Counillon, Liping Zhang, Paul-Arthur Monerie, Viatcheslav Kharin, Simona Flavoni, Juliette Mignot, Panos Athanasiadis, Didier Swingedouw, Thomas L. Delworth, Louis-Philippe Caron, Francisco J. Doblas-Reyes, Met Office Hadley Centre for Climate Change (MOHC), United Kingdom Met Office [Exeter], College of Engineering, Mathematics and Physical Sciences [Exeter] (EMPS), University of Exeter, Centro Euro-Mediterraneo per i Cambiamenti Climatici [Bologna] (CMCC), Bjerknes Centre for Climate Research (BCCR), Department of Biological Sciences [Bergen] (BIO / UiB), University of Bergen (UiB)-University of Bergen (UiB), Barcelona Supercomputing Center - Centro Nacional de Supercomputacion (BSC - CNS), Océan et variabilité du climat (VARCLIM), Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (LOCEAN), Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-Institut de Recherche pour le Développement (IRD)-Muséum national d'Histoire naturelle (MNHN)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-Institut de Recherche pour le Développement (IRD)-Muséum national d'Histoire naturelle (MNHN)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU), Nansen Environmental and Remote Sensing Center [Bergen] (NERSC), National Center for Atmospheric Research [Boulder] (NCAR), NOAA Geophysical Fluid Dynamics Laboratory (GFDL), National Oceanic and Atmospheric Administration (NOAA), Institució Catalana de Recerca i Estudis Avançats (ICREA), Canadian Centre for Climate Modelling and Analysis (CCCma), Environment and Climate Change Canada, Atmosphere and Ocean Research Institute [Kashiwa-shi] (AORI), The University of Tokyo (UTokyo), Department of Earth and Planetary Sciences [Fukuoka], Kyushu University [Fukuoka], Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Max-Planck-Institut für Meteorologie (MPI-M), Max-Planck-Gesellschaft, Deutscher Wetterdienst [Offenbach] (DWD), Environnements et Paléoenvironnements OCéaniques (EPOC), Observatoire aquitain des sciences de l'univers (OASU), Université Sciences et Technologies - Bordeaux 1-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Sciences et Technologies - Bordeaux 1-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS), European Project: 776613,Fighting and adapting to climate change,H2020-EU.3.5.1,EUCP(2017), European Project: 727852,Blue-Action(2016), Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)-Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Kyushu University, Université Sciences et Technologies - Bordeaux 1 (UB)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Sciences et Technologies - Bordeaux 1 (UB)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-École Pratique des Hautes Études (EPHE), Barcelona Supercomputing Center, Smith D.M., Scaife A.A., Eade R., Athanasiadis P., Bellucci A., Bethke I., Bilbao R., Borchert L.F., Caron L.-P., Counillon F., Danabasoglu G., Delworth T., Doblas-Reyes F.J., Dunstone N.J., Estella-Perez V., Flavoni S., Hermanson L., Keenlyside N., Kharin V., Kimoto M., Merryfield W.J., Mignot J., Mochizuki T., Modali K., Monerie P.-A., Muller W.A., Nicoli D., Ortega P., Pankatz K., Pohlmann H., Robson J., Ruggieri P., Sospedra-Alfonso R., Swingedouw D., Wang Y., Wild S., Yeager S., Yang X., and Zhang L.

Subjects
010504 meteorology & atmospheric sciences, Atmospheric circulation, Climatologia -- Models matemàtics, SEASONAL PREDICTIONS, ATMOSPHERIC CIRCULATION, DECADAL PREDICTION, OSCILLATION, VARIABILITY, SKILL, CMIP5, NAO, INITIALIZATION, UNCERTAINTY, Climate change, [PHYS.PHYS.PHYS-GEO-PH]Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph], Climatology--Computer programs, 010502 geochemistry & geophysics, 01 natural sciences, Climate models, Predictable signal, Simulació per ordinador, Projection of climate change, Precipitation, ComputingMilieux_MISCELLANEOUS, 0105 earth and related environmental sciences, Desenvolupament humà i sostenible [Àrees temàtiques de la UPC], Decadal predictions, Multidisciplinary, Mode (statistics), Variance (land use), Computer simulation, Climatic changes, 13. Climate action, North Atlantic oscillation, Climatology, North Atlantic atmospheric circulation, Environmental science, Errors-in-variables models, Climate model
Abstract

Quantifying signals and uncertainties in climate models is essential for the detection, attribution, prediction and projection of climate change1,2,3. Although inter-model agreement is high for large-scale temperature signals, dynamical changes in atmospheric circulation are very uncertain4. This leads to low confidence in regional projections, especially for precipitation, over the coming decades5,6. The chaotic nature of the climate system7,8,9 may also mean that signal uncertainties are largely irreducible. However, climate projections are difficult to verify until further observations become available. Here we assess retrospective climate model predictions of the past six decades and show that decadal variations in North Atlantic winter climate are highly predictable, despite a lack of agreement between individual model simulations and the poor predictive ability of raw model outputs. Crucially, current models underestimate the predictable signal (the predictable fraction of the total variability) of the North Atlantic Oscillation (the leading mode of variability in North Atlantic atmospheric circulation) by an order of magnitude. Consequently, compared to perfect models, 100 times as many ensemble members are needed in current models to extract this signal, and its effects on the climate are underestimated relative to other factors. To address these limitations, we implement a two-stage post-processing technique. We first adjust the variance of the ensemble-mean North Atlantic Oscillation forecast to match the observed variance of the predictable signal. We then select and use only the ensemble members with a North Atlantic Oscillation sufficiently close to the variance-adjusted ensemble-mean forecast North Atlantic Oscillation. This approach greatly improves decadal predictions of winter climate for Europe and eastern North America. Predictions of Atlantic multidecadal variability are also improved, suggesting that the North Atlantic Oscillation is not driven solely by Atlantic multidecadal variability. Our results highlight the need to understand why the signal-to-noise ratio is too small in current climate models10, and the extent to which correcting this model error would reduce uncertainties in regional climate change projections on timescales beyond a decade. DMS, AAS, NJD, LH and RE were supported by the Met Office Hadley Centre Climate Programme funded by BEIS and Defra and by the European Commission Horizon 2020 EUCP project (GA 776613). FJDR, LPC, SW and RB also acknowledge the support from the EUCP project (GA 776613) and from the Ministerio de Econom´ıa y Competitividad (MINECO) as part of the CLINSA project (Grant No. CGL2017-85791-R). SW received funding from the innovation programme under the Marie Sk´lodowska-Curie grant agreement H2020-MSCA-COFUND-2016-754433 and PO from the Ramon y Cajal senior tenure programme of MINECO. The EC-Earth simulations were performed on Marenostrum 4 (hosted by the Barcelona Supercomputing Center, Spain) using Auto-Submit through computing hours provided by PRACE.WAM, HP, KMand KP were supported by the German FederalMinistry for Education and Research (BMBF) project MiKlip (grant 01LP1519A). NK, IB, FC and YW were supported by the Norwegian Research Council projects SFE (grant 270733) the Nordic Center of excellent ARCPATH (grant 76654) and the Trond Mohn Foundation, under the project number : BFS2018TMT01 and received grants for computer time from the Norwegian Program for supercomputing (NOTUR2, NN9039K) and storage grants (NORSTORE, NS9039K). JM, LFB and DS are supported by Blue-Action (European Union Horizon 2020 research and innovation program, Grant Number: 727852) and EUCP (European Union Horizon 2020 research and innovation programme under grant agreement no 776613) projects. The National Center for Atmospheric Research (NCAR) is a major facility sponsored by the US National Science Foundation (NSF) under Cooperative Agreement No. 1852977. NCAR contribution was partially supported by the National Oceanic and Atmospheric Administration (NOAA) Climate Program Office under Climate Variability and Predictability Program Grant NA13OAR4310138 and by the US NSF Collaborative Research EaSM2 Grant OCE-1243015.

Published
2020

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